Accuracy Evaluation of Altimeter-Derived Gravity Field Models in Offshore and Coastal Regions of China

Satellite radar altimetry has made unique contributions to global and coastal gravity field recovery. This paper starts with a general introduction followed by the progress of satellite radar altimetry technology. Then, the methods of marine gravity field recovery and dominating gravity models are described briefly. Finally, typical gravity models are compared with shipboard gravity measurements to evaluate their accuracies in offshore and coastal regions of China. The root mean squares of deviations between gravity models and shipboard gravity are all more than 7 mGal in offshore regions and within the range of 9.5–10.2 mGal in coastal regions. Further analysis in coastal regions indicates that the new gravity models with new satellite missions including Jason-2, SARAL/Altika, and Envisat data have relatively higher accuracy, especially SARAL/Altika data, significantly improving the coastal gravity field. Accuracies are low in areas with strong currents, showing that tide correction is very important for altimetry-derived marine gravity recovery as well as shipboard measurements in coastal gravity field determination. Moreover, as an external check, shipboard gravity data need more operations to improve their precision, such as higher instrument accuracy and finer data processing.

Coastal Sea Level Trends from a Joint Use of Satellite Radar Altimetry, GPS and Tide Gauges: Case Study of the Northern Adriatic Sea

For the last century, tide gauges have been used to measure sea level change along the world’s coastline. However, tide gauges are heterogeneously distributed and sparse in coverage. The measured sea level changes are also affected by solid-Earth geophysics. Since 1992, satellite radar altimetry technique made possible to measure heights at sea independent of land changes. Recently various efforts started to improve the sea level record reprocessing past altimetry missions to create an almost 30 year-long combined record for sea level research studies. Moreover, coastal altimetry, i.e. the extension of altimetry into the oceanic coastal zone and its exploitation for looking at climate-scale variations of sea level, has had a steady progress in recent years and has become a recognized mission target for present and future satellite altimeters. Global sea level rise is today well acknowledged. On the opposite, the regional and local patterns are much more complicated to observe and explain. Sea level falls in some places and rises in others, as a consequence of natural cycles and anthropogenic causes. As relative sea level height continues to increase, many coastal cities can have the local elevation closer to the flooding line. It is evident that at land-sea interface a single technique is not enough to de-couple land and sea level changes. Satellite radar altimetry and tide gauges would coincide at coast if land had no vertical motion. By noting this fact, the difference of the two independent measurements is a proxy of land motion. In this chapter, we review recent advances in open ocean and coastal altimetry to measure sea level changes close to the coasts over the satellite radar altimetry era. The various methods to measure sea level trends are discussed, with focus on a more robust inverse method that has been tested in the Northern Adriatic Sea, where Global Positioning System (GPS) data are available to conduct a realistic assessment of uncertainties. The results show that the classical approach of estimating Vertical Land Motion (VLM) provides values that are almost half of those provided by the new Linear Inverse Problem With Constraints (LIPWC) method, in a new formulation which makes use of a change of variable (LIPWCCOV). Moreover, the accuracy of the new VLM estimates is lower when compared to the VLM estimated from GPS measurements. The experimental Sea Level Climate Change Initiative (SLCCI) data set (high resolution along track) coastal sea level product (developed within Climate Change Initiative (CCI project) that has been also assessed in the Gulf of Trieste show that the trends calculated with the gridded and along track datasets exhibit some differences, probably due to the different methodologies used in the generation of the products.

Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records

A total of 13 satellite missions have been launched since 1985, with different types of radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the root mean square error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.

Surface circulation in the Ligurian Sea: an assessment of satellite radar altimeter-derived geostrophic currents.

<p>Recent improvements of satellite altimeter observations allow to approach investigations on the surface ocean circulation even in those regions where the slope associated to dynamic structures is reduced. The capability to detect the main dynamic features and their variability from satellite radar altimetry in the Ligurian Sea (Western Mediterranean) is here assessed.</p><p>Altimeter data from X-TRACK products recently released are used for this study: the time series of satellite-based- currents along the track n.044, which crosses the Ligurian Sea from the Corsica Channel to the Ligurian coast, is analysed. The temporal sampling is about 10 days and the along-track resolution is 7 km. Geostrophic currents computed from satellite radar altimetry are checked for consistency against the dynamic topography obtained from concurrent CTD casts collected during recent oceanographic campaigns carried out by the Italian Hydrographic Institute along the track. A more detailed assessment of the computed current velocities is based on the analysis of long-term ADCP measurements from a fixed mooring deployed from 2004 to 2006 in the Central Ligurian Sea (43°47.77’ N; 9°02.85’ E) 40 nm from the coast, quite close to the altimeter track. An RD&I 300 kHz upward-looking ADCP sampled the upper layer at 8 m vertical resolution. Currents in the upper layer (0-100 m) are almost barotropic with the variability due to the wind confined to the upper few meters. In order to define an appropriate metrics to compare currents from different measuring systems, EOF analysis of ADCP profiles have proved to be a good tool to filter out the high frequency and wind driven currents, thus enhancing the contribution of the geostrophic component.</p>

GNSS Profile from the Greenland Korth Expeditions in the Context of Satellite Data

Over the last two decades, a small group of researchers repeatedly crossed the Greenland interior skiing along a 700-km long route from east to west, acquiring precise GNSS measurements at exactly the same locations. Four such elevation profiles of the ice sheet measured in 2002, 2006, 2010 and 2015 were differenced and used to analyze the surface elevation change. Our goal is to compare such locally measured GNSS data with independent satellite observations. First, we show an agreement in the rate of elevation change between the GNSS data and satellite radar altimetry (ERS, Envisat, CryoSat-2). Both datasets agree well (2002–2015), and both correctly display local features such as an elevation increase in the central part of the ice sheet and a sharp gradual decline in the surface heights above Jakobshavn Glacier. Second, we processed satellite gravimetry data (GRACE) in order for them to be comparable with local GNSS measurements. The agreement is demonstrated by a time series at one of the measurement sites. Finally, we provide our own satellite gravimetry (GRACE, GRACE-FO, Swarm) estimate of the Greenland mass balance: first a mild decrease (2002–2007: −210 ± 29 Gt/yr), then an accelerated mass loss (2007–2012: −335 ± 29 Gt/yr), which was noticeably reduced afterwards (2012–2017: −178 ± 72 Gt/yr), and nowadays it seems to increase again (2018–2019: −278 ± 67 Gt/yr).

Evaluation of Historic and Operational Satellite Radar Altimetry Missions for Constructing Consistent Long-term Lake Water Level Records

Thirteen satellite missions have been launched since 1985, with different types of radar altimeters onboard. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over twelve lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the Root Mean Square Error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g. OCOG/Ice-1/Ice) outperform the model-based retrackers for all missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISat has slightly better lake water level estimates than Jason-1 and -2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than Topex/Poseidon mission. In contrast, for large lakes Topex/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have extremely high data missing rate. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission between 1985 and 1990 that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with Topex/Poseidon, Jason-1 and Jason-3 and then normalize them to form a consistent Topex/Poseidon-Jason series. Then, use Topex/Poseidon-Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.

Surface Properties Linked to Retrieval Uncertainty of Satellite Sea-Ice Thickness with Upward-Looking Sonar Measurements

One of the key sources of uncertainties in sea ice freeboard and thickness estimates derived from satellite radar altimetry results from changes in sea ice surface properties. In this study, we analyse this effect, comparing upward-looking sonar (ULS) measurements in the Beaufort Sea over the period 2003–2018 to sea ice draft derived from Envisat and Cryosat-2 data. We show that the sea ice draft growth underestimation observed for the most of winter seasons depends on the surface properties preconditioned by the melt intensity during the preceding summer. The comparison of sea ice draft time series in the Cryosat-2 era indicates that applying 50% retracker thresholds, used to produce the European Space Agency’s Climate Change Initiative (CCI) product, provide better agreement between satellite retrievals and ULS data than the 80% threshold that is closer to the expected physical waveform interpretation. Our results, therefore, indicate compensating error contributions in the full end-to-end sea-ice thickness processing chain, which prevents the quantification of individual factors with sea-ice thickness/draft validation data alone.